An interpretable classifier for detection of cardiac arrhythmias by using the fuzzy decision tree

Autor:	Mohammed Amine Chikh, Omar Behadada
Rok vydání:	2013
Předmět:	Fuzzy decision Medical knowledge business.industry Computer science Cardiac activity General Medicine Machine learning computer.software_genre Fuzzy decision tree cardiovascular system Artificial intelligence Data mining Medical diagnosis business Classifier (UML) computer
Zdroj:	Artificial Intelligence Research. 2
ISSN:	1927-6982 1927-6974
DOI:	10.5430/air.v2n3p45
Popis:	An extraction of medical knowledge from cardiological data is proposed in this work, it is based on relevant intelligent method called fuzzy decision tree. It could lead to increase understanding the cause of various abnormal beats in cardiac activity, leading to a better medical diagnosis. The performance of this technique is evaluated on the MIT-BIH Arrhythmia Database following the AAMI recommendations. The first part of this paper discusses the characterization of heart beats. It is considered as an important step in arrhythmias classification. In a second part we apply the fuzzy decision tree to recognize some cardiac abnormalities. In the last part we discuss the activity of fuzzy decision rules extracted from cardiological data analyzing.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::2f95d15d521612362b939e9fe75a951c https://doi.org/10.5430/air.v2n3p45 Zobrazit plný text záznamu